ArticleBMC psychiatry2022
An explanatory model of depressive symptoms from anxiety, post-traumatic stress, somatic symptoms, and symptom perception: the potential role of inflammatory markers in hospitalized COVID-19 patients.
Article in BMC psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Psychiatric symptoms of long COVID among adults: observational case-control study in Johannesburg, South Africa.BJPsych open · 2026Article
- Concurrent depression and anxiety in women undergoing additional diagnostic procedures due to positive screening for cervical cancer.PloS one · 2026Observational
- The Role of Religious Involvement as a Moderator of Perceived Health and Somatic Anxiety Among Hispanic Seventh-Day Adventists During COVID-19.Journal of religion and health · 2025Article
- Post-pandemic mental health: Understanding the global psychological burden and charting future research priorities.World journal of psychiatry · 2025Review
- The regulation mechanism of perceived stress on cognitive function of patients with breast cancer undergoing chemotherapy: a multiple mediation analysis.Breast cancer research and treatment · 2025Article
- Examining the relationship between inflammatory biomarkers during COVID-19 hospitalization and subsequent long-COVID symptoms: A longitudinal and retrospective study.Immunity, inflammation and disease · 2023Article
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6 authors at 4 institutions in 1 country.
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Abstract
backgroundThe context of the COVID-19 pandemic has harmed the mental health of the population, increasing the incidence of mental health problems such as depression, especially in those who have had COVID-19. Our study puts forward an explanatory model of depressive symptoms based on subjective psychological factors in those hospitalized for COVID-19 with and without biological markers (i.e., inflammatory markers). Therefore, we aim to evaluate the hypotheses proposed in the model to predict the presence of depressive symptoms.
methodWe conducted a cross-sectional study, using a simple random sampling. Data from 277 hospitalized patients with COVID-19 in Lima-Peru, were collected to assess mental health variables (i.e., depressive, anxiety, post-traumatic stress, and somatic symptoms), self-perception of COVID-19 related symptoms, and neutrophil/lymphocyte ratio (NLR) such as inflammatory marker. We performed a structural equation modeling analysis to evaluate a predictive model of depressive symptoms.
resultsThe results showed a prevalence of depressive symptoms (11.2%), anxiety symptoms (7.9%), somatic symptoms (2.2%), and symptoms of post-traumatic stress (6.1%) in the overall sample. No association was found between the prevalence of these mental health problems among individuals with and without severe inflammatory response. The mental health indicators with the highest prevalence were sleep problems (48%), low energy (47.7%), nervousness (48.77%), worry (47.7%), irritability (43.7%) and back pain (52%) in the overall sample. The model proposed to explain depressive symptoms was able to explain more than 83.7% of the variance and presented good goodness-of-fit indices. Also, a different performance between the proposed model was found between those with and without severe inflammatory response. This difference was mainly found in the relationship between anxiety and post-traumatic stress symptoms, and between the perception of COVID-19 related symptoms and somatic symptoms.
conclusionsResults demonstrated that our model of mental health variables may explain depressive symptoms in hospitalized patients of COVID-19 from a third-level hospital in Peru. In the model, perception of symptoms influences somatic symptoms, which impact both anxiety symptoms and symptoms of post-traumatic stress. Thus, anxiety symptoms could directly influence depressive symptoms or through symptoms of post-traumatic stress. Our findings could be useful to decision-makers for the prevention of depression, used to inform the creation of screening tools (i.e., perception of symptoms, somatic and anxiety symptoms) to identify vulnerable patients to depression.
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